{
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    "colab": {
      "name": "All_Regimes_WTA.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyP7MLDpRAVzXB0fBm/ImFTa",
      "include_colab_link": true
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    "kernelspec": {
      "name": "python3",
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    }
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Divyanshu-ISM/Oil-and-Gas-data-analysis/blob/master/All_Regimes_WTA.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "klU7nxj5vyuQ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NqgZs1R9wBI2",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df = pd.read_csv('all.txt',sep='\\t')"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DoRnjYOEwkMp",
        "colab_type": "code",
        "colab": {
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          "height": 204
        },
        "outputId": "0fd00b0f-3063-418b-f7d5-a4ca2d0f8124"
      },
      "source": [
        "df['dP'] = np.zeros(len(df))\n",
        "\n",
        "df['dP'][0] = 5000 - df['p'][0]\n",
        "\n",
        "df['dP'][1:] = abs(np.diff(df['p']))\n",
        "\n",
        "df.head()"
      ],
      "execution_count": 22,
      "outputs": [
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              "          t        p     dP\n",
              "0  0.000100  4992.57   7.43\n",
              "1  0.000212  4983.91   8.66\n",
              "2  0.000339  4974.73   9.18\n",
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          "height": 204
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        "outputId": "648c4774-6c7b-4203-99e7-a7f3b0f27c70"
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        "df['dt'] = np.zeros(len(df))\n",
        "\n",
        "df['dt'][0] = df['t'][0]\n",
        "\n",
        "df['dt'][1:] = abs(np.diff(df['t']))\n",
        "\n",
        "df.head()"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
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            "text/plain": [
              "          t        p     dP        dt\n",
              "0  0.000100  4992.57   7.43  0.000100\n",
              "1  0.000212  4983.91   8.66  0.000112\n",
              "2  0.000339  4974.73   9.18  0.000127\n",
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              "4  0.000642  4953.53  11.20  0.000160"
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        "colab_type": "code",
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          "height": 204
        },
        "outputId": "428f0781-86e0-4319-c3bf-155817ab9f43"
      },
      "source": [
        "df['tdP/dt'] = df['t']*df['dP']/df['dt']\n",
        "\n",
        "df.head()"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "          t        p     dP        dt     tdP/dt\n",
              "0  0.000100  4992.57   7.43  0.000100   7.430000\n",
              "1  0.000212  4983.91   8.66  0.000112  16.357778\n",
              "2  0.000339  4974.73   9.18  0.000127  24.593272\n",
              "3  0.000481  4964.73  10.00  0.000142  33.813614\n",
              "4  0.000642  4953.53  11.20  0.000160  44.863069"
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          "execution_count": 24
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          "height": 204
        },
        "outputId": "9b64a5a3-919a-46b1-a684-b87bf701618c"
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      "source": [
        "df['t_1/2'] = np.sqrt(df['t'])\n",
        "\n",
        "df['t_1/4'] = np.sqrt(df['t_1/2'])\n",
        "\n",
        "df['t_(-1/2)'] = (df['t'])**(-0.5)\n",
        "\n",
        "df.head()"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th>4</th>\n",
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              "      <td>4953.53</td>\n",
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            "text/plain": [
              "          t        p     dP  ...     t_1/2     t_1/4    t_(-1/2)\n",
              "0  0.000100  4992.57   7.43  ...  0.010000  0.100000  100.000000\n",
              "1  0.000212  4983.91   8.66  ...  0.014577  0.120737   68.599434\n",
              "2  0.000339  4974.73   9.18  ...  0.018414  0.135697   54.307499\n",
              "3  0.000481  4964.73  10.00  ...  0.021942  0.148128   45.574998\n",
              "4  0.000642  4953.53  11.20  ...  0.025330  0.159155   39.478353\n",
              "\n",
              "[5 rows x 8 columns]"
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          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
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    {
      "cell_type": "code",
      "metadata": {
        "id": "quNyMveU2gYB",
        "colab_type": "code",
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          "height": 204
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        "outputId": "e81b1633-95c2-4eb1-e3e2-4f6557fbc340"
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      "source": [
        "df['d(t_1/2)'] = df['t_1/2']\n",
        "\n",
        "df['d(t_1/2)'][1:] = abs(np.diff(df['d(t_1/2)']))\n",
        "\n",
        "df['dP/dt_1/2'] = df['dP']/df['d(t_1/2)']\n",
        "\n",
        "df.head()"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
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              "      <td>0.000142</td>\n",
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              "      <td>0.003528</td>\n",
              "      <td>2834.313213</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
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              "      <td>4953.53</td>\n",
              "      <td>11.20</td>\n",
              "      <td>0.000160</td>\n",
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            ],
            "text/plain": [
              "          t        p     dP  ...    t_(-1/2)  d(t_1/2)    dP/dt_1/2\n",
              "0  0.000100  4992.57   7.43  ...  100.000000  0.010000   743.000000\n",
              "1  0.000212  4983.91   8.66  ...   68.599434  0.004577  1891.912076\n",
              "2  0.000339  4974.73   9.18  ...   54.307499  0.003836  2392.940876\n",
              "3  0.000481  4964.73  10.00  ...   45.574998  0.003528  2834.313213\n",
              "4  0.000642  4953.53  11.20  ...   39.478353  0.003388  3305.314340\n",
              "\n",
              "[5 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "L5-lMU5C3a5E",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "ac449392-c615-4ed2-fb18-21152efbb420"
      },
      "source": [
        "df['d(t_1/4)'] = df['t_1/4']\n",
        "\n",
        "df['d(t_1/4)'][1:] = abs(np.diff(df['d(t_1/4)']))\n",
        "\n",
        "df['dP/dt_1/4'] = df['dP']/df['d(t_1/4)']\n",
        "\n",
        "df.head()"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>t</th>\n",
              "      <th>p</th>\n",
              "      <th>dP</th>\n",
              "      <th>dt</th>\n",
              "      <th>tdP/dt</th>\n",
              "      <th>t_1/2</th>\n",
              "      <th>t_1/4</th>\n",
              "      <th>t_(-1/2)</th>\n",
              "      <th>d(t_1/2)</th>\n",
              "      <th>dP/dt_1/2</th>\n",
              "      <th>d(t_1/4)</th>\n",
              "      <th>dP/dt_1/4</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.000100</td>\n",
              "      <td>4992.57</td>\n",
              "      <td>7.43</td>\n",
              "      <td>0.000100</td>\n",
              "      <td>7.430000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.100000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>743.000000</td>\n",
              "      <td>0.100000</td>\n",
              "      <td>74.300000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.000212</td>\n",
              "      <td>4983.91</td>\n",
              "      <td>8.66</td>\n",
              "      <td>0.000112</td>\n",
              "      <td>16.357778</td>\n",
              "      <td>0.014577</td>\n",
              "      <td>0.120737</td>\n",
              "      <td>68.599434</td>\n",
              "      <td>0.004577</td>\n",
              "      <td>1891.912076</td>\n",
              "      <td>0.020737</td>\n",
              "      <td>417.614656</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.000339</td>\n",
              "      <td>4974.73</td>\n",
              "      <td>9.18</td>\n",
              "      <td>0.000127</td>\n",
              "      <td>24.593272</td>\n",
              "      <td>0.018414</td>\n",
              "      <td>0.135697</td>\n",
              "      <td>54.307499</td>\n",
              "      <td>0.003836</td>\n",
              "      <td>2392.940876</td>\n",
              "      <td>0.014960</td>\n",
              "      <td>613.630861</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.000481</td>\n",
              "      <td>4964.73</td>\n",
              "      <td>10.00</td>\n",
              "      <td>0.000142</td>\n",
              "      <td>33.813614</td>\n",
              "      <td>0.021942</td>\n",
              "      <td>0.148128</td>\n",
              "      <td>45.574998</td>\n",
              "      <td>0.003528</td>\n",
              "      <td>2834.313213</td>\n",
              "      <td>0.012431</td>\n",
              "      <td>804.448345</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.000642</td>\n",
              "      <td>4953.53</td>\n",
              "      <td>11.20</td>\n",
              "      <td>0.000160</td>\n",
              "      <td>44.863069</td>\n",
              "      <td>0.025330</td>\n",
              "      <td>0.159155</td>\n",
              "      <td>39.478353</td>\n",
              "      <td>0.003388</td>\n",
              "      <td>3305.314340</td>\n",
              "      <td>0.011027</td>\n",
              "      <td>1015.666599</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          t        p     dP  ...    dP/dt_1/2  d(t_1/4)    dP/dt_1/4\n",
              "0  0.000100  4992.57   7.43  ...   743.000000  0.100000    74.300000\n",
              "1  0.000212  4983.91   8.66  ...  1891.912076  0.020737   417.614656\n",
              "2  0.000339  4974.73   9.18  ...  2392.940876  0.014960   613.630861\n",
              "3  0.000481  4964.73  10.00  ...  2834.313213  0.012431   804.448345\n",
              "4  0.000642  4953.53  11.20  ...  3305.314340  0.011027  1015.666599\n",
              "\n",
              "[5 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "d-JfEfKv3zXO",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "5be1431f-dabf-469d-9220-2bc6be5e39ff"
      },
      "source": [
        "df['d(t_-0.5)'] = df['t_(-1/2)']\n",
        "\n",
        "df['d(t_-0.5)'][1:] = abs(np.diff(df['d(t_-0.5)']))\n",
        "\n",
        "df['dP/dt_(-1/2)'] = df['dP']/df['d(t_-0.5)']\n",
        "\n",
        "df.head()"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>t</th>\n",
              "      <th>p</th>\n",
              "      <th>dP</th>\n",
              "      <th>dt</th>\n",
              "      <th>tdP/dt</th>\n",
              "      <th>t_1/2</th>\n",
              "      <th>t_1/4</th>\n",
              "      <th>t_(-1/2)</th>\n",
              "      <th>d(t_1/2)</th>\n",
              "      <th>dP/dt_1/2</th>\n",
              "      <th>d(t_1/4)</th>\n",
              "      <th>dP/dt_1/4</th>\n",
              "      <th>d(t_-0.5)</th>\n",
              "      <th>dP/dt_(-1/2)</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.000100</td>\n",
              "      <td>4992.57</td>\n",
              "      <td>7.43</td>\n",
              "      <td>0.000100</td>\n",
              "      <td>7.430000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.100000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>743.000000</td>\n",
              "      <td>0.100000</td>\n",
              "      <td>74.300000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>0.074300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.000212</td>\n",
              "      <td>4983.91</td>\n",
              "      <td>8.66</td>\n",
              "      <td>0.000112</td>\n",
              "      <td>16.357778</td>\n",
              "      <td>0.014577</td>\n",
              "      <td>0.120737</td>\n",
              "      <td>68.599434</td>\n",
              "      <td>0.004577</td>\n",
              "      <td>1891.912076</td>\n",
              "      <td>0.020737</td>\n",
              "      <td>417.614656</td>\n",
              "      <td>31.400566</td>\n",
              "      <td>0.275791</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.000339</td>\n",
              "      <td>4974.73</td>\n",
              "      <td>9.18</td>\n",
              "      <td>0.000127</td>\n",
              "      <td>24.593272</td>\n",
              "      <td>0.018414</td>\n",
              "      <td>0.135697</td>\n",
              "      <td>54.307499</td>\n",
              "      <td>0.003836</td>\n",
              "      <td>2392.940876</td>\n",
              "      <td>0.014960</td>\n",
              "      <td>613.630861</td>\n",
              "      <td>14.291935</td>\n",
              "      <td>0.642320</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.000481</td>\n",
              "      <td>4964.73</td>\n",
              "      <td>10.00</td>\n",
              "      <td>0.000142</td>\n",
              "      <td>33.813614</td>\n",
              "      <td>0.021942</td>\n",
              "      <td>0.148128</td>\n",
              "      <td>45.574998</td>\n",
              "      <td>0.003528</td>\n",
              "      <td>2834.313213</td>\n",
              "      <td>0.012431</td>\n",
              "      <td>804.448345</td>\n",
              "      <td>8.732500</td>\n",
              "      <td>1.145147</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.000642</td>\n",
              "      <td>4953.53</td>\n",
              "      <td>11.20</td>\n",
              "      <td>0.000160</td>\n",
              "      <td>44.863069</td>\n",
              "      <td>0.025330</td>\n",
              "      <td>0.159155</td>\n",
              "      <td>39.478353</td>\n",
              "      <td>0.003388</td>\n",
              "      <td>3305.314340</td>\n",
              "      <td>0.011027</td>\n",
              "      <td>1015.666599</td>\n",
              "      <td>6.096645</td>\n",
              "      <td>1.837076</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          t        p     dP  ...    dP/dt_1/4   d(t_-0.5)  dP/dt_(-1/2)\n",
              "0  0.000100  4992.57   7.43  ...    74.300000  100.000000      0.074300\n",
              "1  0.000212  4983.91   8.66  ...   417.614656   31.400566      0.275791\n",
              "2  0.000339  4974.73   9.18  ...   613.630861   14.291935      0.642320\n",
              "3  0.000481  4964.73  10.00  ...   804.448345    8.732500      1.145147\n",
              "4  0.000642  4953.53  11.20  ...  1015.666599    6.096645      1.837076\n",
              "\n",
              "[5 rows x 14 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-dI0o9OJ5klg",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        },
        "outputId": "5ef1a541-fb12-4541-d801-03943bffcc86"
      },
      "source": [
        "plt.figure(figsize=(12,4))"
      ],
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Figure size 864x288 with 0 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 42
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 864x288 with 0 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BQxIZIR64P4P",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 569
        },
        "outputId": "13b59b0d-7730-46fe-afca-317d18e32c10"
      },
      "source": [
        "plt.figure(figsize=(12,6))\n",
        "plt.style.use('default')\n",
        "\n",
        "\n",
        "plt.loglog(df['t'],df['tdP/dt'],label='Radial Flow(Derivative)',marker='d')\n",
        "\n",
        "plt.loglog(df['t'],df['dP/dt_1/2'],label='t1/2',marker='.',alpha=0.3)\n",
        "\n",
        "plt.loglog(df['t'],df['dP/dt_1/4'],label='1/4',marker='*',alpha=0.3)\n",
        "\n",
        "plt.loglog(df['t'],df['dP/dt_(-1/2)'],label='t_(-0.5)',marker='x')\n",
        "\n",
        "plt.loglog(df['t'],abs(5000-df['p']),label='Pressure',linewidth='3',marker='v',color='black')\n",
        "\n",
        "plt.axvline(x=0.001,label='End of WBS',color='m',linewidth=3)\n",
        "\n",
        "# plt.axvline(x=0.3)\n",
        "# plt.axvline(x=2)\n",
        "plt.axvspan(0.3,2.0,alpha=0.5,label='Spherical Flow',color='y')\n",
        "plt.axvspan(0.0001,0.001,alpha=0.5,label='WBS(Unit Slope)')\n",
        "plt.axvspan(10,70,alpha=0.5,label='IARF(Radial Flow)',color='orange')\n",
        "\n",
        "plt.xlabel('Time(log Axis)')\n",
        "plt.ylabel('Pressure Related Stuff(log axis)')\n",
        "\n",
        "plt.title('Well Test Analysis - Diagnostic Plot')\n",
        "plt.legend(loc='best')\n",
        "\n",
        "plt.grid()\n",
        "\n"
      ],
      "execution_count": 78,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8m85Wg6j4n9X",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}